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| United States Patent |
6,096,553
|
|
Heald
, et al.
|
August 1, 2000
|
On-line analysis of acid catalyst in an alkylation process
Abstract
A computer implemented method for on-line determination of concentrations
in an HF alkylation process catalyst stream containing HF acid, ASO, water
and optionally an additive which suppresses the vapor pressure of HF acid.
The method employs near-infrared spectroscopy coupled with chemometric
data analysis. The data analysis uses a partial least squares regression
technique which determines unknown concentrations based on spectral
calibration data. In use, an absorbance spectrum of material is obtained,
e.g., from a slipstream taken from the process alkylation catalyst stream,
and the detected spectrum is mathematically analyzed with the aid of the
computer to simultaneously predict concentration of HF acid, ASO, water
and optionally the additive which suppresses the vapor pressure of HF
acid.
| Inventors:
|
Heald; Randall L. (209 Skycrest, Borger, TX 79007);
Eastman; Alan Dan (3209 Wilson Rd., Bartlesville, OK 74006);
Randolph; Bruce B. (233 Turkey Creek Rd., Bartlesville, OK 74006);
Renfro; Donald H. (4342 SE. Adams, Bartlesville, OK 74006)
|
| Appl. No.:
|
208219 |
| Filed:
|
December 9, 1998 |
| Current U.S. Class: |
436/40; 250/339.12; 422/82.09; 436/60; 436/139; 436/171 |
| Intern'l Class: |
G01N 021/59 |
| Field of Search: |
436/55,60,61,139,40,171
422/62,82.09
250/339.12,339.08,339.01,340
|
References Cited
U.S. Patent Documents
| 3935097 | Jan., 1976 | Roof | 210/31.
|
| 4009998 | Mar., 1977 | Benningfield, Jr. | 23/230.
|
| 4207423 | Jun., 1980 | Makovec et al. | 422/111.
|
| 5407830 | Apr., 1995 | Altman et al. | 436/55.
|
| 5583049 | Dec., 1996 | Altman et al. | 436/55.
|
| 5681749 | Oct., 1997 | Ramamoorthy | 436/55.
|
Primary Examiner: Snay; Jeffrey
Attorney, Agent or Firm: Richmond, Hitchcock, Fish & Dollar
Parent Case Text
This application claims the benefit of U.S. provisional application Ser.
No. 60/069,867 filed Dec. 17, 1997.
Claims
That which is claimed is:
1. A method for on-line concentration determination of at least three
components in a liquid mixture which contains unknown concentrations of an
acid catalyst for hydrocarbon conversion, an acid-soluble-oil (ASO), and
water, said method for three component determination comprising the
following steps:
(a) recording an electromagnetic absorbance spectrum for said liquid
mixture over the near-infrared wavelength range of from about 1250 nm to
about 2200 nm;
(b) using data from said absorbance spectrum in a chemometric analysis for
determining concentration of said acid catalyst, and said ASO in said
liquid mixture; and
(c) using primarily that portion of data from said absorbance spectrum in a
range of from about 1925 nm to about 1945 nm in said chemometric analysis
for determining concentration of water in said liquid mixture.
2. A method in accordance with claim 1, wherein said liquid mixture is
obtained in a slip stream from a recirculating acid catalyst stream in a
hydrocarbon conversion process and wherein said liquid mixture comprises a
flowing sample stream.
3. A method in accordance with claim 1, wherein said acid catalyst
comprises hydrogen fluoride (HF) acid.
4. A method in accordance with claim 1, wherein said liquid mixture
additionally contains an additive and said method for on-line
concentration determination comprises a quadruple component concentration
determination additionally including the following step:
using data from said absorbance spectrum in a chemometric analysis for
determining concentration of said additive in said liquid mixture.
5. A method in accordance with claim 4, wherein said additive comprises
sulfolane.
6. A method in accordance with claim 1, wherein said electromagnetic
absorbance spectrum is obtained with a spectrometer/analyzer calibrated
with a training set of gravimetrically blended samples, and wherein said
spectrometer/analyzer is calibrated using a leave-one-sample-out
technique.
7. A method in accordance with claim 1, wherein said chemometric analysis
is carried out in a computer programmed with a chemometric model for
determination of said at least three components.
8. Apparatus for on-line concentration determination of at least three
components in a liquid mixture which contains unknown concentration of an
acid catalyst for hydrocarbon conversion, an acid-soluble-oil (ASO), and
water, said apparatus comprising:
(a) means for recording an electromagnetic absorbance spectrum for said
liquid mixture over the near infrared wavelength range from about 1250 nm
to about 2200 nm;
(b) computer means for using data from said absorbance spectrum in a
chemometric analysis for determining concentration of said acid catalyst
and, said ASO in said liquid mixture; and
(c) computer means for using primarily that portion of data from said
absorbance spectrum in a range of from about 1925 nm to about 1945 nm in
said chemometric analysis for determining concentration of water in said
liquid mixture.
9. Apparatus in accordance with claim 8 additionally comprising:
a sample cell; and
a slip stream means for obtaining said liquid mixture from a recirculating
acid catalyst stream in a hydrocarbon conversion process, and passing said
liquid mixture to said sample cell.
10. Apparatus in accordance with claim 8, wherein said liquid mixture
additionally contains an additive and said apparatus for on-line
prediction comprises a quadruple component concentration prediction, said
apparatus additionally including:
computer means using data from said absorbance spectrum in a chemometric
analysis for determining concentration of said additive in said liquid
mixture.
11. Apparatus in accordance with claim 8, wherein said means for recording
said electromagnetic absorbance spectrum for said liquid mixture comprises
a spectrometer/analyzer, said apparatus additionally comprising:
means for calibrating said spectrometer/analyzer comprising a training set
of gravimetrically blended samples, and
wherein said computer means is programmed with a chemometric model for
determination of said at least triple components responsive to said
recorded electromagnetic absorbance spectrum.
Description
The present invention relates to process analytical chemistry using near
infrared spectroscopy, and more particularly to absorption of specific
electromagnetic wavelengths by chemical components in a liquid acid
catalyst mixture.
BACKGROUND OF THE INVENTION
Hydrogen fluoride (HF) alkylation is an important refinery process in which
isobutane is reacted with olefins to produce highly-branched isoparaffins
as illustrated in FIG. 1 for use in gasoline blending. In this process,
hydrofluoric (HF) acid functions as the catalyst and recirculates through
the reactor. The recirculating HF acid catalyst is not pure; it contains a
small amount of water and a reaction byproduct called acid-soluble oil.
The catalyst is also saturated with the hydrocarbons involved in the
process (e.g., alkylate and isobutane). In the HF alkylation process, it
is important to monitor and control the purity of the catalyst since
excessive amounts of water and acid-soluble-oil (ASO) have deleterious
consequences: Excessive water, for example, can cause rapid corrosion of
some carbon steel components.
Controlling the activity of the catalyst requires measuring the
concentrations of HF acid, water, and ASO in a recirculating catalyst
stream. Therefore, prior to this invention operators would take samples of
the catalyst periodically and have these components measured by classical
analytical techniques. There are several problems associated with this
approach. First of all, HF acid will cause serious burns if it contacts
skin. Because of this hazard, collecting and analyzing these samples
carries potential for injury. Another problem is that the analytical
methods used for these measurements lack precision, especially the method
for ASO. This often makes it difficult to determine if the composition of
the catalyst has truly changed from sample to sample. Finally, samples are
drawn from the reactor only once or twice a day, and the analyses require
several hours. This makes it difficult to follow the composition of the
catalyst in a timely manner when processing changes do occur.
In the past few years, there has been a great deal of interest in on-line
monitoring of various refinery process streams. In part, this interest has
been spurred by advances in analytical technology that have greatly
expanded the capabilities for process monitoring.
Accordingly, it is an object of the invention to continuously analyze
hydrocarbon process streams containing acid catalyst, ASO and water.
It is a more specific object of this invention to improve precision and
reduce the time required for analytical chemistry measurements of acid
catalyst, ASO and water.
Yet another object is to reduce exposure of refining personnel to hazardous
process chemicals.
Still another more specific object of this invention is to detect
relatively small changes in ASO and other impurities in a recirculating
catalyst stream that result in reduced catalyst activity.
SUMMARY OF THE INVENTION
A method and apparatus for on-line process chemical analysis yields
three-component concentration values in an alkylation catalyst stream,
which is typically a mixture of acid catalyst, ASO, water, and
hydrocarbons. In accordance with one aspect of the invention, the method
involves using near-infrared spectroscopy in which a spectrometer/analyzer
acquires spectral absorbance data of the recirculating catalyst in an
alkylation process over a wavelength range of about 1250 nm to about 2200
nm. Within this spectral region appear absorption bands associated with
each of the three components of interest e.g., HF acid has a strong broad
absorption band with a maximum peak located at approximately 1390 nm.
Likewise, water has an absorption band centered near 1935 nm. ASO has
associated with it multiple sharp bands located between about 1670 nm and
1850 nm. According to the invention, determination of individual
concentrations of components in the acid catalyst stream relies on a
mathematical analysis of the entire acquired spectral region using a
technique known as partial least squares regression. The determination of
water concentration in an acid catalyst however, relies primarily on a
specific band within the acquired spectral region in a range from about
1925 nm to about 1945 nm. The mathematical analysis of the spectral data,
which is more fully described herein below, is one of a number of known
multivariate analysis techniques, which are referred to collectively as
chemometrics.
In accordance with another aspect of this invention a quadruple-component
chemical analysis yields individual concentrations as indicated above, and
additionally yields concentration of an additive to the recirculating acid
catalyst stream which suppresses the vapor pressure of HF acid. The
presently preferred additive is sulfolane, and in the quadruple
measurement, the wavelength region measured contains additionally three
narrow absorption bands associated with sulfolane. These bands are located
near 1420 nm, 1725 nm, and 1920 nm.
The method and apparatus of this invention, using spectral absorption data
in combination with chemometric analysis of the spectral absorption data,
thus rapidly measure concentration of multiple components in a hazardous
stream with very high precision. Further, the invention eliminates the
need to manually collect samples from the reactor, and the essentially
real-time analysis and high accuracy of the measurement allows operators
and engineers to respond much more quickly to small changes in acid
catalyst composition and/or activity.
Other objects and advantages of the invention will be apparent from the
foregoing brief description of the invention and the appended claims as
well as the detailed description of the drawings which are briefly
described as follows:
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is an illustration of a chemical reaction formula for producing an
alkylate product.
FIG. 2 is a graphical form for illustrating the NIR region of the
electromagnetic spectrum.
FIG. 3 is a schematic diagram illustrating key components used for NIR
spectroscopy.
FIG. 4 is a graph showing the NIR absorbance spectrum of an HF process acid
catalyst stream.
FIG. 5 is a schematic diagram illustrating an NIR analyzer interfaced to a
process stream.
FIG. 6 is a schematic diagram illustrating how NIR spectroscopy and
chemometrics function together.
FIG. 7 is a graph illustrating actual blended concentrations versus NIR
measured concentration for HF acid in a blended mixture of three
components.
FIG. 8 is a graph similar to FIG. 7 showing measured concentration of ASO.
FIG. 9 is a graph similar to FIG. 7 showing measured concentration of
water.
FIG. 10 is illustrating a lab scale reactor system for simulating a
commercial alkylation process.
FIG. 11 is a graph illustrating concentration of HF acid and ASO versus
time on stream in an alkylation process.
FIG. 12 is a graph illustrating concentration of HF acid and water versus
time on stream in an alkylation process.
FIG. 13 is a graph similar to FIG. 11 illustrating extended time on stream.
FIG. 14 is a graph similar to FIG. 12 illustrating extended time on stream.
DETAILED DESCRIPTION OF THE INVENTION
Near-Infrared Spectroscopy
The method and apparatus described in this specification involves an
analytical measurement technique based on near-infrared (NIR)
spectroscopy, which uses electromagnetic radiation in the NIR region shown
in FIG. 4 and in FIG. 2. This region of the spectrum lies between the
visible region where our eyes function and the mid-infrared region where
conventional infrared spectroscopy is performed.
In NIR spectroscopy, as illustrated in FIG. 3, the radiation from a halogen
lamp 30 is caused to pass through a sample contained in a cell 32. In
on-line process analysis, the sample is from the process and can flow
continuously through the cell. After the radiation passes through the
sample, it is dispersed into its various wavelengths by a dispersive
element illustrated at 34. Alternatively, in the case of Fourier transform
spectroscopy, the radiation is modulated by an interferometer. Next, the
dispersed or modulated radiation is detected at the detector 36. Finally,
the detector signal is mathematically converted into a spectrum in which
the amount of radiation absorbed is plotted as function of wavelength.
Such an absorbance spectrum is illustrated in FIG. 4.
As in mid-IR spectroscopy, NIR spectra reflect the chemical structure of
the compound(s) measured. In other words, each different chemical will
have a characteristic absorption spectrum. NIR measurement times are fast,
with results typically updated every one to three minutes, and NIR
spectroscopy is inherently very precise. This is very important in process
monitoring where detecting small changes in the process and following the
associated trends is often of primary interest. NIR instrumentation optics
are very rugged, and instruments often have only one moving part. In
addition, robust optic materials such as quartz and sapphire can be used
in the optical sections. Compatibility with quartz optics allows optical
fibers to be used to convey NIR radiation from the spectrometer to a
remote sample point. This provides a great deal of flexibility in how the
analyzer is interfaced with the process. Optical multiplexing can be used
in conjunction with fiber optics to monitor several sampling points with
the same spectrometer. The combination of all of these features makes NIR
spectroscopy one of the best analytical techniques for on-line process
monitoring. A suitable on-line process analyzer for Fourier transform--IR
application, is available from a company called Applied Automation Inc.
(AAI), Inc. Bartlesville, Okla. 74004. This analyzer includes software
that controls the sampling system, cell washing etc., in addition to
obtaining spectral data.
Chemometrics
Referring now to FIG. 4, the NIR absorption spectrum of a typical HF acid
catalyst is illustrated. FIG. 4 also illustrates the principal difficulty
associated with the use of NIR spectroscopy. This spectrum contains
absorption features that are associated with each of the components of
interest i.e., HF, ASO, and water. Unfortunately, these bands are broad
and overlap extensively. This overlap precludes the use of simple
univariate calibration methods for quantitation of the sample components.
This problem can be overcome by applying more powerful multivariate
mathematical calibration techniques to the analysis of the spectral data.
These multivariate mathematical techniques when applied to process
chemical analysis are collectively referred to as chemometrics. As used
herein chemometrics is the science of relating measurements made on a
chemical system to the state of that system via the application of
mathematical or statistical methods. This technique uses complex
mathematics such as matrix vector algebra and statistics to extract
quantitative information (i.e., concentrations) from highly convoluted or
statistically confounded data. Chemometric analysis is typically performed
in suitable high speed computers running commercially available software
programs. Numerous software packages are currently available, for example,
a program called "Pirouette" can be obtained from Infometrics, Inc., P.O.
Box 1528 Woodinville, Wash. 98072. Pirouette is actually a suite of
chemometric programs, including such methods as K-Nearest Neighbors
analysis (KNN), Heirarchical Cluster Analysis (HCA), Principal Component
Analysis (PCA), Partial Least Squares (PLS) analysis, and Principal
Component Regression (PCR) analysis. Of these various data analysis
methods, the first three are designed for pattern recognition and data
classification. Only the last two, PLS and PCR are designed for
constructing a calibration model and applying it to an instrument response
(e.g., an NIR spectrum) to calculate a property of a sample (e.g.,
concentration of a chemical constituent). Of these two, PLS is most
commonly applied to NIR spectral data because it generally provides the
best calibration models in terms of accuracy.
In practice, quantitative NIR analysis using chemometrics requires fairly
extensive calibration. This calibration is achieved by analyzing a set of
samples with known values for all of the properties to be measured by NIR.
These calibration samples are frequently characterized by a reference
measurement method. In cases where the composition of the sample is
relatively simple or the reference method suffers from poor precision,
synthetic blends can be used for calibration. Regardless of how the
properties are determined, the calibration sample set is generally
referred to as the training set. The results for the training set (i.e.,
the NIR spectra and reference data) are used to build a calibration model
using the multivariate calibration procedure. Once a suitable model is
built, it is used to calculate the property or properties of interest from
the NIR absorption spectra of unknown samples. This entire calibration
process is diagramed in FIG. 6. Although somewhat complex, when properly
executed this approach can be accurate, precise and robust.
For a discussion of chemometric techniques see, for example, Sharaf, M. A.
Illmaen, D. L. and Kowalski, B. R., "Chemometrics", Wiley, New York, 1986.
Analyzer Configuration
NIR analyzers can be interfaced with a process in a wide variety of
configurations. One approach is shown in FIG. 5.
In this approach, the sample cell is located in a slip stream, and thus
sample conditioning such as filtering and thermostating is possible prior
to the analysis. Using an optical fiber interface maintains the ability to
locate the analyzer in a remote location.
EXAMPLE 1.
This example successfully demonstrates in a laboratory environment the
feasibility of measuring three components including HF acid, ASO, and
water contained in an HF process catalyst stream. FIGS. 7-9 show the
correlations between the concentrations of these components calculated
from the NIR data and the corresponding gravimetrically blended
concentrations. In these figures, each NIR data point is the result of a
cross-validation analysis, which is performed as follows: One at a time,
each sample in the training set is excluded from the calibration set. A
chemometric model is created from the remaining sample data. This model is
then used to calculate the concentration (e.g., wt % HF acid) associated
with the excluded sample. The excluded data is returned to the calibration
set and another sample is excluded. A new model is generated and used to
calculate a new result and error (difference between calculated result and
known value). This leave-one-out process is continued for every sample in
the training set.
The accumulated errors from the cross-validation analysis are used to
calculate a standard error of cross validation (standard deviation of the
errors), SEV. The SEV for each measured component is listed in upper
left-hand corner of FIGS. 7-9. These values represent the standard
deviations between the NIR and the blended concentrations, which were used
as standard values, and thus reflect the accuracy of the NIR method. The
demonstrated accuracy is very good for all three components.
Although agreement between the on-line analyzer and the laboratory methods
is necessary, precision is more important in most applications. This is
true because measurement precision determines just how small a process
change can be reliably detected. As Table I below shows, the NIR method's
precision is outstanding compared to the previously used lab methods. For
each of the three components, the repeatability of the NIR measurement
shows a 30- to 50-fold improvement over that of the corresponding lab
method.
TABLE I
______________________________________
Measurement Precision Comparison
Component NIR Lab Method
______________________________________
HF Acid 0.1% 3%
ASO 2% 80%
Water 0.5% 30%
______________________________________
All calibration runs were carried out using a bench-scale riser reactor
with a settler and acid catalyst recirculation as shown in FIG. 10. The
sample cell used for all spectroscopic measurements was installed between
the acid catalyst heat exchanger and the recirculation pump. For each
calibration run, known amounts of HF, water, and ASO were blended and
transferred to the reactor. Refinery alkylate and isobutane were added to
the reactor and the material was recirculated under conditions similar to
those found in the full-scale alkylation process.
An Applied Automation Advance FTIR Analyzer was used for all NIR
spectroscopic measurements. The sample cell was constructed of Hasteloy-C
with sapphire windows. The analyzer was coupled to the sample cell using
low-OH quartz optical fiber. The spectral data was processed using a
partial least squares algorithm available in the commercial chemometric
software. The experimental design included 16 gravimetric blends that
spanned a concentration range greater than that normally encountered in an
actual alkylation unit. Table II below lists the concentration ranges for
each of the three components.
TABLE II
______________________________________
NIR Calibration with 16 Gravimetric Blends
Component RANGE
______________________________________
HF Acid 80-100 wt. %
ASO 0-15 wt. %
Water 0-5 wt. %
______________________________________
EXAMPLE 2
The laboratory scale alkylation unit used in the previous example is
illustrated in FIG. 10 and is more fully described below. This laboratory
unit includes a riser reactor 100, a feed dispersion device which is not
illustrated, an acid settler 102, an acid recirculation pump 104, and
product collection equipment generally illustrated at 106. The same
equipment was used in this example to successfully demonstrate laboratory
scale operation at simulated process conditions. The NIR data were
collected with a flow cell 108 mounted between the acid heat exchanger 110
and acid pump 104, such that all of the acid inventory flows through the
cell 108 during each pass around the reactor. For each run, a pre-blended
feed of olefins and isobutane was introduced to the reactor via the feed
inlet 112. Starting acid concentration was 98% HF acid and starting water
was 2% by weight. The acid/hydrocarbon emulsion from the reactor 100 is
routed to the settler 102, where the acid phases out to the bottom and is
recirculated to the reactor. Product hydrocarbon is withdrawn from the top
of the settler 102, and then scrubbed to remove any HF acid, and then
collected for analysis. Acid samples are withdrawn intermittently for HF
acid and ASO determination to provide a comparison for NIR values.
Selected results for Run #1 are given in Table III below. The feed to the
reactor 100 is a blend of refinery supplied olefins and isobutane. A feed
introduction device is installed in order to increase the amount of ASO
produced over that normally observed. This allowed enough ASO to be
generated for a good comparison between NIR and standard techniques.
TABLE III
______________________________________
NIR and Traditional Acid Test Results: MTBE-Free Feed
TOS* (Hours) 20 44 68 92
______________________________________
% HF (titration)
89.3 93.0 86.6 88.4
% ASO (extn) 0.85 1.25 2.09 2.52
% H2O (NIR) 1.80 2.00 2.19 2.06
TOTAL 92.0 96.3 90.9 93.0
% HF (NIR) 91.81 90.22 88.69 88.01
% ASO (NIR) 0.391 1.78 3.12 3.92
% H2O (NIR) 1.80 2.00 2.19 2.06
TOTAL 94.0 94.0 94.0 94.0
______________________________________
*Time On Stream
Standard HF titrations (dilution and titration to phenolpthalein endpoint)
generally gave values within 2-3 wt % of the NIR values. The ASO
concentrations determined by extraction (after neutralization) were
usually only 50-70% of the NIR values. This was expected, however, because
the NIR measures total ASO, while the extraction measures mostly heavier
ASO (vide infra). Water was not analyzed by an independent method;
however, the concentrations determined by NIR varied only within a fairly
narrow range (1.8 and 2.2 wt %). FIGS. 11 and 12 show the trend lines
associated with HF, ASO, and water versus increasing times on stream.
After 92 hours, the feed was spiked with 570 ppm MTBE
(methyltert-butylether) (or.about.7000 ppm based on olefin only). MTBE is
commonly produced upstream of the alkylation unit as an oxygenate for RFG
(reformulated gasoline). Under normal operation the concentration of MTBE
in the alkylation feed is nil, but under upset conditions, levels of
1000-5000 ppm are possible and can have rapid, deleterious consequences
for acid purity due to accelerated ASO production. Table IV gives the
results for the acid analysis at selected times on stream. Again the HF
acid concentration values from NIR are within 1-2 wt % of the titration
values. Note the 70% increase in ASO concentration between 92 hours (Table
III) and 113 hours (Table IV), reflecting the high propensity for ASO
production from MTBE. The increase in ASO based on traditional data was
only about 33%. Both the NIR and traditional concentration data show an
increase in ASO with time, but again with traditional tests we observed
only about 50-65% of the total ASO determined by NIR. Water remained
relatively constant until acid purity was increased after 167 hours. At
this time, the catalyst was nearly deactivated, necessitating a reduction
of ASO and water and an increase in HF concentration. FIGS. 13 and 14 show
the trend lines for HF, ASO, and water with the MTBE-containing feeds.
TABLE IV
______________________________________
NIR and Traditional Acid Test Results: 570 ppm MTBE-Feed
TOS (Hours) 113 143 167 191
______________________________________
% HF (titration)
87.3 86.4 84.2 86.0
% ASO (extn) 3.35 4.0 4.7 4.7
% H2O (NIR) 2.01 2.08 2.01 1.78
TOTAL 92.7 92.5 90.9 92.5
% HF (NIR) 85.3 84.4 83.3 85.0
% ASO (NIR) 6.71 7.51 8.73 7.28
% H2O (NIR) 2.01 2.08 2.01 1.78
TOTAL 94.0 94.0 94.0 94.0
______________________________________
One of the key advantages of NIR is the fast response time, and in the
present work, spectra were taken every six minutes (times as short as 1
spectrum per minute are possible). The inherent precision of NIR is
another significant advantage, showing a 30- to 50-fold improvement in
repeatability when compared to the traditional laboratory test methods for
HF, water, and ASO. The current technique allows the rapid determination
of HF, ASO, and water directly and independently of each other, in the
presence of other dissolved/dispersed non-ASO hydrocarbons such as C3,
iC4, nC4, C5+ alkylate, etc. This is a result of the method in which the
training set data were collected. The NIR results add to 94% since the raw
data was normalized to reflect the usual rule of 6% hydrocarbon
dissolved/dispersed in the acid phase. In all cases, the sum of the raw
data for HF acid, ASO, and water was between 99.6 and 100.1%, even though
the chemometric model was not constrained to limit that result. In
traditional analyses, the difference between 94% and the sum of the acid
components is taken as an indication of light ASO. As these data show, the
traditional tests give an indication of about 1-3% light ASO (the
titration value of 93% at 44 hours is likely an outlier). The NIR
technique is set up (by design) to measure both light and heavy ASO. This
is the reason for the discrepancy between NIR predictions and extraction
measurements. Lighter ASO components are frequently lost during sample
preparation for traditional tests.
The "spikes" present in FIGS. 11-14 occurred when acid was either added to
or withdrawn from the reactor. These spikes in the trend lines result from
the formation of gas/vapor bubbles which form inside the cell. Nitrogen is
used as a pressure source for acid addition and to also maintain constant
unit pressure. Accordingly, as acid is withdrawn or added, a pressure
differential results. The cell, which is located between the acid cooler
110 and the magnetically driven acid recirculation gear pump 104, is
susceptible to N2 gas bubble formation in the acid line. If bubbles
develop, they can easily be trapped in the cell, since all of the acid in
the system is routed through the cell. The gas bubbles cause rapid changes
in the optical pathlength, resulting in wildly fluctuating values. The
bubbles could be removed from the system by manipulation of the acid flow
rate. Accordingly gas/vapor bubble formation is a phenomenon related to
the experimental set-up in the laboratory.
While this invention has been described in terms of the presently preferred
embodiment for on-line analysis of four components including HF acid, ASO,
water and sulfolane in an HF alkylation process, the same analyzer might
be used to analyze other process streams. In an alkylation process, a
number of other measurements could be made. These might include
concentration measurements of the alkylate product as well as the
isobutane and olefin feed stream.
For the alkylate product stream, it is common practice to periodically
sample and measure the research octane number (RON) as well as
concentration of trimethylpentanes (TMP's) and dimenthylhexanes (DMH's),
and these variables can be measured with excellent results using NIR
techniques. NIR could also be used to monitor the isobutane-to-olefin
ratio in the feed or the purity of the isobutane recycle stream.
Accordingly, reasonable variations and modifications are possible by those
skilled in the art, and such modification and variations are within the
scope of the described invention and the appended claims.
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